Distributors face complex pressures today, from global market volatility and supply chain disruption to inflation, rising energy costs and the need to continually exceed customer expectations. They also need to find better ways to attract and retain top talent while, at the same time, streamlining operations to be competitive.
Industry 4.0 technologies, such as artificial intelligence (AI), Machine Learning (ML), and Internet of Things (IoT) can help distributors address this myriad of challenges. Such technologies are already facilitating a range of innovations for the distribution industry. And more importantly, advancements are making these technologies more attainable to a greater number of organizations.
Distributors are poised to leverage AI and ML to improve customer service and respond faster to demand fluctuations, utilize IoT to offer integrated supply and new pricing models, and implement tools to provide greater automation, limiting the impact of ongoing labor shortages. Whether it’s AI, ML, or IoT, there are numerous benefits to leveraging these innovative technologies.
Leveraging AI & ML to improve customer service
There are countless ways for organizations to mine the data they’ve collected, but historically it has proven to be too pricey or time consuming to be worth the investment. With AI and ML, making accumulated data actionable and delivering value are now attainable goals. With these technologies in place, distributors can more easily anticipate the future needs of customers based upon past and present activity and make product recommendations tailored to each customer’s needs and preferences.
To help illustrate this benefit, it is helpful to discuss the use case of Midwest Wheel Companies, one of the largest truck parts distributors in the Midwestern U.S. The company had to manage complex operations during its continued growth, ensuring delivery to all its customers at the target rate of service. The company implemented a product recommendation engine using Infor Coleman AI and ML to ensure complimentary products were considered during customer engagements. This seamless approach ensures the customer’s anticipated needs are met and the customer experiences the best possible interaction, even when new employees are involved. The system provides the depth of knowledge, even when the employee has yet to attain it.
Previously, some of the company’s customers lost time at the sales counter, or over the phone, when salespeople had to manually search for the right interdependent parts to order for repairs. In some cases, customers needed to come back and place orders for more parts if they didn’t get all they needed the first time. Further, salespersons sometimes missed additional sales opportunities because they weren’t always familiar with all the combinations of parts that are commonly sold together.
As a result of deploying Infor AI and ML technologies, Midwest Wheel significantly improved customer satisfaction and employee productivity – reducing sales order processing time by 30% and helping customers save money by ordering the right mix of parts.
Reducing costs and responding faster to demand fluctuations
Technology innovation will also play a role in managing demand fluctuations. When demand can be better anticipated, it will inform purchasing decisions so that inventory discrepancies are minimized.
Distributors need to have the right amount of inventory at any given time because there is a cost associated with having too much or too little inventory. Historically, it was critical for distributors to leverage a solution that enabled flexibility to look at demand by accumulating demand metrics over multiple years. Using these metrics, a distributor estimated demand projections based on previous customer demand for certain products.
But as the technology has evolved, it’s now possible to use modern AI and ML algorithms to weave in more real-time external factors such as weather, social media, shifting trends, and impacts from the pandemic to become even more accurate. This insight can be extremely valuable to distributors focused on any marginal advantage. Better forecasting will result in fewer lost sales due to lack of inventory and improved customer satisfaction and retention.
Using integrated supply to change customer relationships
One way to solidify a partnership with a customer is to implement an integrated supply or vendor managed inventory (VMI) relationship. In this scenario, both the distributor and their customer agree in advance that certain inventory will be managed and maintained directly by the distributor at the customer’s location. This guarantee ensures that critical parts are always in stock and easily accessible to that customer.
While the intricacies of this kind of engagement previously might have been cost prohibitive, new technologies promoting greater transparency, automation, and IoT have made VMI partnerships very attractive. A key use case for illustrating this benefit centers on the practice of leveraging day-to-day buying patterns through IoT and automating replenishment of products based on collected daily insights. This way, a distributor receives an automated message of what inventory was used each day. Based on what was used, the message will trigger replenishment and billing activities.
The distributor uses its expertise in inventory management to remove a burden or risk from the customer while securing a stronger long-term contractual relationship, as that customer is then unlikely to shop around for the same items elsewhere. And the customer is satisfied that its critical components are always in stock and at their fingertips. This level of automation is beneficial for both parties.
Improving margin accuracy to increase revenue
In an industry accustomed to operating under intense margin pressure, setting the right price for specific products has never been more critical to sustaining business growth and day-to-day performance.
With AI making an increasingly powerful appearance in business processes and management tools, it can take over many of the dull and time-consuming tasks that workers used to put up with, such as continuously reviewing pricing strategies and monitoring sales data to identify margin anomalies or trends.
A company that used to spend hundreds of hours to make sure there were no errors in the margins is Pilot Flying J. Pilot’s fuel margins are significant as they drive much of the bottom line and profit. An error in fuel pricing at a location, can lead to either lost customers because the price is too high or lost revenue through low pricing for customers who would have visited anyway.
Pilot Flying J partnered with Infor to use Infor Coleman Machine Learning (ML) to automate this manual, time-consuming, and potentially error-prone fuel margin anomaly checking process in the finance department. Pilot ran Coleman machine learning on 36 months of historical data residing in the Infor Data Lake to highlight fuel margin anomalies—any line item that calculates a large difference in the machine generated margin to the actual margin.
Today, instead of tediously looking at thousands of lines within a report to check for fuel margin errors, the finance team looks at dashboards that visually presents the few anomalies that need human investigation and resolution, saving the equivalent of two FTE’s and bringing the margin accuracy up to 99.99%.
Implementing automation tools to empower employees
For years distributors have been struggling to attract and retain top talent. Recently, changes in employee expectations have risen to such a degree that the labor shortage is of primary concern across distributors of all sizes.
One way distributors are addressing this issue is with technology investments that automate processes, so they can do more without increasing headcount. With a cloud solution, the primary tasks associated with managing and maintaining the systems become the solution provider’s responsibility. Once you’re in the cloud, new opportunities arise with AI and ML projects that can distill large amounts of data into actionable insights. Even something as simple as accounts receivable automation uses AI technology to streamline the process, resulting in better cash flow results. Or, greater investments can be made in robotics and warehouse automation systems to increase productivity. In addition, an investment in modern technology can help create a better working environment that empowers employees with the information they need to do their jobs more effectively. Making everyday tasks easier is a great way to increase job satisfaction and hold onto the talent you currently have while enticing new hires to join you.
Distributors have better access to Industry 4.0 technologies than ever before, and these technologies can pave the way for them to offer a host of value-added services to their customers. With technologies such as AI, ML and IoT, distributors can use data-driven insights to improve customer service, better manage demand fluctuations and inventory in real-time to boost customer satisfaction, and quickly detect margin anomalies. Moreover, by using Industry 4.0 technologies to automate certain processes, distributors enable employees to focus on higher-value work, increasing job satisfaction and enabling their organizations to attract and retain talent more effectively.
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